Computational Modeling and Pharmacokinetics/ADMET Study of Some Arylpiperazine Derivatives as Novel Antipsychotic Agents Targeting Depression

Publication: Chemistry Africa
Software: ADMET Predictor®


This study focuses on Quantitative structure–activity relationship (QSAR) and in silico pharmacokinetics/ADMET predictions to investigate the structural features and pharmacokinetic/ADMET properties that influenced the antipsychotic activity of some arylpiperazine derivatives as inhibitors of Serotonin Transporter (SERT) for antidepressant agents. Density Functional Theory approach (DFT/B3LYP/6-31G*) via Spartan 14 V1.1.4 software was used for the geometry optimization of the compounds while the Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) in Material studio software were used for variable selection and development of QSAR models. The statistical analysis and validation parameters of the best model (R 2Train = 0.944, R 2Test = 0.637, Q 2cv = 0.895, cRp2 = 0.845 and RMSE = 0.100) shows that the model was predictive, reliable, robust and very stable. More so, molecular descriptors; SpMax6_Bhm, VP-3, geomDiameter, RDF35i and E1e were significantly contributed to the observed antipsychotic activities of the compounds with SpMax6_Bhm (37.5%) played a predominant role and positively correlated to the observed antipsychotic property of the compounds. Similarly, the in silico pharmacokinetics/ADMET investigations revealed that the selected compounds portend to be orally bioavailable, highly absorbed by the gastrointestinal system and could permeate into the brain with low ADMET risk. Likewise, all the selected compounds were inhibitors of CYP2C19 and CYP2D6 cytochromes P450 (CYP) enzymes and none of the selected compounds exhibit human ether-a-go-go-related gene (hERG) cardiovascular toxicity. Hence, the model possessed good quality assurance and satisfied OECD Principles for model development. In consequence, the physicochemical and pharmacokinetic parameters/properties derived from this study could be considered when developing other arylpiperazine derivatives with improved activity as antidepressant agents.

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